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Modify device_map behavior when loading a model using from_pretrained (#23922)

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* Modify device map behavior for 4/8 bits model

* Remove device_map arg for training 4/8 bit model

* Remove index

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Add Exceptions

* Modify comment

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Fix formatting

* Get current device with accelerate

* Revert "Get current device with accelerate"

This reverts commit 46f00799103bbe15bd58762ba029aab35363c4f7.

* Fix Exception

* Modify quantization doc

* Fix error

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

---------

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
This commit is contained in:
Marc Sun
2023-06-01 13:21:22 -04:00
committed by GitHub
parent d1fa349e78
commit e03a9cc0cd
5 changed files with 59 additions and 18 deletions
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4
tests/bitsandbytes/test_4bit.py
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@@ -429,7 +429,9 @@ class Bnb4BitTestTraining(Base4bitTest):
return
# Step 1: freeze all parameters
model = AutoModelForCausalLM.from_pretrained(self.model_name, load_in_4bit=True, device_map="auto")
model = AutoModelForCausalLM.from_pretrained(self.model_name, load_in_4bit=True)
self.assertEqual(set(model.hf_device_map.values()), {torch.cuda.current_device()})
for param in model.parameters():
param.requires_grad = False # freeze the model - train adapters later